Overview

Dataset statistics

Number of variables13
Number of observations378
Missing cells57
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.9 KiB
Average record size in memory108.0 B

Variable types

Numeric12
Categorical1

Alerts

Close is highly overall correlated with High and 4 other fieldsHigh correlation
High is highly overall correlated with Close and 4 other fieldsHigh correlation
Low is highly overall correlated with Close and 4 other fieldsHigh correlation
MA_10 is highly overall correlated with Close and 4 other fieldsHigh correlation
MA_20 is highly overall correlated with Close and 4 other fieldsHigh correlation
Open is highly overall correlated with Close and 4 other fieldsHigh correlation
Return is highly overall correlated with open-closeHigh correlation
Volume is highly overall correlated with low-highHigh correlation
low-high is highly overall correlated with VolumeHigh correlation
open-close is highly overall correlated with ReturnHigh correlation
MA_10 has 9 (2.4%) missing valuesMissing
Volatility_10 has 9 (2.4%) missing valuesMissing
MA_20 has 19 (5.0%) missing valuesMissing
Volatility_20 has 19 (5.0%) missing valuesMissing
Volume has unique valuesUnique

Reproduction

Analysis started2024-07-06 14:57:00.173253
Analysis finished2024-07-06 14:57:16.787935
Duration16.61 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Open
Real number (ℝ)

HIGH CORRELATION 

Distinct362
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.64204
Minimum126.01
Maximum221.64999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:16.911471image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum126.01
5-th percentile143.85
Q1169.0425
median177.8
Q3189.33
95-th percentile196.89999
Maximum221.64999
Range95.639992
Interquartile range (IQR)20.287502

Descriptive statistics

Standard deviation17.459125
Coefficient of variation (CV)0.098839015
Kurtosis0.54361136
Mean176.64204
Median Absolute Deviation (MAD)10.540001
Skewness-0.48644437
Sum66770.69
Variance304.82105
MonotonicityNot monotonic
2024-07-06T10:57:17.197891image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181.2700043 3
 
0.8%
189.3300018 2
 
0.5%
176.4799957 2
 
0.5%
184.8999939 2
 
0.5%
196.8999939 2
 
0.5%
182.3500061 2
 
0.5%
171.75 2
 
0.5%
165.1900024 2
 
0.5%
191.5700073 2
 
0.5%
180.0700073 2
 
0.5%
Other values (352) 357
94.4%
ValueCountFrequency (%)
126.0100021 1
0.3%
126.8899994 1
0.3%
127.1299973 1
0.3%
130.2599945 1
0.3%
130.2799988 1
0.3%
130.4700012 1
0.3%
131.25 1
0.3%
132.0299988 1
0.3%
133.8800049 1
0.3%
134.0800018 1
0.3%
ValueCountFrequency (%)
221.6499939 1
0.3%
220 1
0.3%
217.5899963 1
0.3%
216.1499939 1
0.3%
215.7700043 1
0.3%
214.7400055 1
0.3%
214.6900024 1
0.3%
213.9299927 1
0.3%
213.8500061 1
0.3%
213.3699951 1
0.3%

High
Real number (ℝ)

HIGH CORRELATION 

Distinct366
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean178.30339
Minimum127.77
Maximum226.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:17.357053image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum127.77
5-th percentile146.451
Q1170.49
median179.66
Q3190.25751
95-th percentile198.2555
Maximum226.45
Range98.68
Interquartile range (IQR)19.767509

Descriptive statistics

Standard deviation17.449549
Coefficient of variation (CV)0.097864373
Kurtosis0.62428283
Mean178.30339
Median Absolute Deviation (MAD)10.32
Skewness-0.40389096
Sum67398.68
Variance304.48676
MonotonicityNot monotonic
2024-07-06T10:57:17.519783image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187.1000061 2
 
0.5%
180.1199951 2
 
0.5%
189.9900055 2
 
0.5%
174.3000031 2
 
0.5%
187.0500031 2
 
0.5%
182.7599945 2
 
0.5%
147.2299957 2
 
0.5%
174.0299988 2
 
0.5%
194.3999939 2
 
0.5%
194.7599945 2
 
0.5%
Other values (356) 358
94.7%
ValueCountFrequency (%)
127.7699966 1
0.3%
128.6600037 1
0.3%
130.2899933 1
0.3%
130.8999939 1
0.3%
131.2599945 1
0.3%
133.4100037 1
0.3%
133.5099945 1
0.3%
134.2599945 1
0.3%
134.9199982 1
0.3%
136.25 1
0.3%
ValueCountFrequency (%)
226.4499969 1
0.3%
221.5500031 1
0.3%
220.3800049 1
0.3%
220.1999969 1
0.3%
218.9499969 1
0.3%
218.6300049 1
0.3%
217.5099945 1
0.3%
216.75 1
0.3%
216.0700073 1
0.3%
215.7400055 1
0.3%

Low
Real number (ℝ)

HIGH CORRELATION 

Distinct373
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.28757
Minimum124.17
Maximum221.64999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:17.693037image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum124.17
5-th percentile142.76451
Q1168.0375
median176.665
Q3187.945
95-th percentile195.3715
Maximum221.64999
Range97.479996
Interquartile range (IQR)19.907501

Descriptive statistics

Standard deviation17.370934
Coefficient of variation (CV)0.099099634
Kurtosis0.59772508
Mean175.28757
Median Absolute Deviation (MAD)10.414993
Skewness-0.51690258
Sum66258.7
Variance301.74934
MonotonicityNot monotonic
2024-07-06T10:57:17.865656image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
177.6000061 2
 
0.5%
194.1399994 2
 
0.5%
182.4400024 2
 
0.5%
172.0500031 2
 
0.5%
170.7599945 2
 
0.5%
193.1699982 1
 
0.3%
182.7299957 1
 
0.3%
181.5 1
 
0.3%
180.1699982 1
 
0.3%
180.8800049 1
 
0.3%
Other values (363) 363
96.0%
ValueCountFrequency (%)
124.1699982 1
0.3%
124.7600021 1
0.3%
124.8899994 1
0.3%
125.0800018 1
0.3%
128.1199951 1
0.3%
129.8899994 1
0.3%
130.4600067 1
0.3%
131.4400024 1
0.3%
131.6600037 1
0.3%
133.7700043 1
0.3%
ValueCountFrequency (%)
221.6499939 1
0.3%
219.0299988 1
0.3%
215.1000061 1
0.3%
213 1
0.3%
212.7200012 1
0.3%
212.3500061 1
0.3%
211.9199982 1
0.3%
211.6000061 1
0.3%
211.3000031 1
0.3%
210.6399994 1
0.3%

Close
Real number (ℝ)

HIGH CORRELATION 

Distinct365
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.88466
Minimum125.02
Maximum226.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:18.042007image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum125.02
5-th percentile145.157
Q1169.005
median178.185
Q3189.425
95-th percentile197.62851
Maximum226.34
Range101.32
Interquartile range (IQR)20.419994

Descriptive statistics

Standard deviation17.381786
Coefficient of variation (CV)0.098266215
Kurtosis0.64641171
Mean176.88466
Median Absolute Deviation (MAD)10.294998
Skewness-0.45040973
Sum66862.4
Variance302.12647
MonotonicityNot monotonic
2024-07-06T10:57:18.219366image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194.5 2
 
0.5%
176.0800018 2
 
0.5%
175.8399963 2
 
0.5%
163.7599945 2
 
0.5%
177.9700012 2
 
0.5%
179.8000031 2
 
0.5%
178.8500061 2
 
0.5%
173.75 2
 
0.5%
169.3000031 2
 
0.5%
173.5 2
 
0.5%
Other values (355) 358
94.7%
ValueCountFrequency (%)
125.0199966 1
0.3%
125.0699997 1
0.3%
126.3600006 1
0.3%
129.6199951 1
0.3%
130.1499939 1
0.3%
130.7299957 1
0.3%
133.4100037 1
0.3%
133.4900055 1
0.3%
134.7599945 1
0.3%
135.2100067 1
0.3%
ValueCountFrequency (%)
226.3399963 1
0.3%
221.5500031 1
0.3%
220.2700043 1
0.3%
216.75 1
0.3%
216.6699982 1
0.3%
214.2899933 1
0.3%
214.2400055 1
0.3%
214.1000061 1
0.3%
213.25 1
0.3%
213.0700073 1
0.3%

Volume
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct378
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61133003
Minimum24048300
Maximum2.464214 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:18.460000image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum24048300
5-th percentile40844405
Q148095625
median55077500
Q367734600
95-th percentile99866845
Maximum2.464214 × 108
Range2.223731 × 108
Interquartile range (IQR)19638975

Descriptive statistics

Standard deviation22842703
Coefficient of variation (CV)0.37365582
Kurtosis17.203105
Mean61133003
Median Absolute Deviation (MAD)9063950
Skewness3.2386622
Sum2.3108275 × 1010
Variance5.2178907 × 1014
MonotonicityNot monotonic
2024-07-06T10:57:18.733818image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112117500 1
 
0.3%
34049900 1
 
0.3%
49128400 1
 
0.3%
46792900 1
 
0.3%
42841800 1
 
0.3%
59144500 1
 
0.3%
62303300 1
 
0.3%
71983600 1
 
0.3%
58414500 1
 
0.3%
82488700 1
 
0.3%
Other values (368) 368
97.4%
ValueCountFrequency (%)
24048300 1
0.3%
28919300 1
0.3%
31458200 1
0.3%
34049900 1
0.3%
34648500 1
0.3%
35175100 1
0.3%
36294600 1
0.3%
37122800 1
0.3%
37266700 1
0.3%
37283200 1
0.3%
ValueCountFrequency (%)
246421400 1
0.3%
198134300 1
0.3%
172373300 1
0.3%
163224100 1
0.3%
154357300 1
0.3%
136682600 1
0.3%
128256700 1
0.3%
121946500 1
0.3%
121664700 1
0.3%
118339000 1
0.3%

open-close
Real number (ℝ)

HIGH CORRELATION 

Distinct310
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.24261894
Minimum-13.5
Maximum5.6800079
Zeros0
Zeros (%)0.0%
Negative211
Negative (%)55.8%
Memory size5.9 KiB
2024-07-06T10:57:18.936178image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-13.5
5-th percentile-3.0230034
Q1-1.5050087
median-0.13999939
Q31.0200043
95-th percentile2.9190033
Maximum5.6800079
Range19.180008
Interquartile range (IQR)2.525013

Descriptive statistics

Standard deviation2.0220199
Coefficient of variation (CV)-8.3341386
Kurtosis4.8930509
Mean-0.24261894
Median Absolute Deviation (MAD)1.2399979
Skewness-0.73488637
Sum-91.709961
Variance4.0885645
MonotonicityNot monotonic
2024-07-06T10:57:19.169017image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5599975586 4
 
1.1%
1.080001831 3
 
0.8%
-0.1399993896 3
 
0.8%
-0.04000854492 3
 
0.8%
-0.3600006104 3
 
0.8%
-0.1100006104 3
 
0.8%
0.08000183105 3
 
0.8%
1.550003052 2
 
0.5%
0.6399993896 2
 
0.5%
-0.6399993896 2
 
0.5%
Other values (300) 350
92.6%
ValueCountFrequency (%)
-13.5 1
0.3%
-6.699996948 1
0.3%
-6.470001221 1
0.3%
-5.990005493 1
0.3%
-5.700012207 1
0.3%
-4.690002441 1
0.3%
-4.660003662 1
0.3%
-4.419998169 1
0.3%
-4.120010376 1
0.3%
-4.009994507 1
0.3%
ValueCountFrequency (%)
5.680007935 1
0.3%
5.489990234 1
0.3%
5.209999084 1
0.3%
5.150009155 1
0.3%
4.289993286 1
0.3%
4.25 1
0.3%
4.099990845 1
0.3%
3.779998779 1
0.3%
3.769989014 1
0.3%
3.529998779 1
0.3%

low-high
Real number (ℝ)

HIGH CORRELATION 

Distinct273
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.0158203
Minimum-13.529999
Maximum-0.95999146
Zeros0
Zeros (%)0.0%
Negative378
Negative (%)100.0%
Memory size5.9 KiB
2024-07-06T10:57:19.409126image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-13.529999
5-th percentile-5.4430031
Q1-3.3800011
median-2.7100067
Q3-2.2224998
95-th percentile-1.4870049
Maximum-0.95999146
Range12.570007
Interquartile range (IQR)1.1575012

Descriptive statistics

Standard deviation1.4206058
Coefficient of variation (CV)-0.47105122
Kurtosis15.862463
Mean-3.0158203
Median Absolute Deviation (MAD)0.59000397
Skewness-2.9570998
Sum-1139.9801
Variance2.0181209
MonotonicityNot monotonic
2024-07-06T10:57:19.658484image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.580001831 5
 
1.3%
-2.330001831 4
 
1.1%
-2.820007324 4
 
1.1%
-2.660003662 4
 
1.1%
-2.419998169 4
 
1.1%
-1.809997559 4
 
1.1%
-2.130004883 4
 
1.1%
-3.330001831 3
 
0.8%
-2.550003052 3
 
0.8%
-2.429992676 3
 
0.8%
Other values (263) 340
89.9%
ValueCountFrequency (%)
-13.52999878 1
0.3%
-13.30000305 1
0.3%
-9.550003052 1
0.3%
-8.080001831 1
0.3%
-7.380004883 1
0.3%
-7.300003052 1
0.3%
-6.910003662 1
0.3%
-6.729995728 1
0.3%
-6.650009155 1
0.3%
-6.229995728 1
0.3%
ValueCountFrequency (%)
-0.9599914551 1
0.3%
-1.059997559 2
0.5%
-1.11000061 1
0.3%
-1.130004883 1
0.3%
-1.199996948 1
0.3%
-1.230010986 1
0.3%
-1.260009766 1
0.3%
-1.339996338 1
0.3%
-1.36000061 1
0.3%
-1.399993896 1
0.3%

MA_10
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct369
Distinct (%)100.0%
Missing9
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean176.97331
Minimum130.455
Maximum214.758
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:20.022495image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum130.455
5-th percentile148.6262
Q1170.072
median177.631
Q3188.757
95-th percentile195.7418
Maximum214.758
Range84.303003
Interquartile range (IQR)18.685001

Descriptive statistics

Standard deviation15.750536
Coefficient of variation (CV)0.088999498
Kurtosis0.39573509
Mean176.97331
Median Absolute Deviation (MAD)9.6549988
Skewness-0.5368355
Sum65303.153
Variance248.07939
MonotonicityNot monotonic
2024-07-06T10:57:20.287727image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192.225 1
 
0.3%
184.2049988 1
 
0.3%
184.5009995 1
 
0.3%
185.3909988 1
 
0.3%
186.1569992 1
 
0.3%
186.912999 1
 
0.3%
187.598999 1
 
0.3%
188.4449997 1
 
0.3%
189.3569992 1
 
0.3%
190.7220001 1
 
0.3%
Other values (359) 359
95.0%
(Missing) 9
 
2.4%
ValueCountFrequency (%)
130.4549988 1
0.3%
131.4689995 1
0.3%
132.3599998 1
0.3%
133.6449997 1
0.3%
134.7940002 1
0.3%
136.0320007 1
0.3%
137.1450012 1
0.3%
138.1920013 1
0.3%
139.4440002 1
0.3%
140.2680008 1
0.3%
ValueCountFrequency (%)
214.7580017 1
0.3%
213.0920013 1
0.3%
212.3660004 1
0.3%
212.0059998 1
0.3%
211.9420013 1
0.3%
211.8390015 1
0.3%
211.5800003 1
0.3%
211.2290009 1
0.3%
209.6339996 1
0.3%
208.5089996 1
0.3%

Volatility_10
Real number (ℝ)

MISSING 

Distinct369
Distinct (%)100.0%
Missing9
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean3.0982561
Minimum0.7065527
Maximum9.7076821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:20.528096image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.7065527
5-th percentile1.3279567
Q12.0480856
median2.760061
Q33.6627122
95-th percentile6.0015563
Maximum9.7076821
Range9.0011294
Interquartile range (IQR)1.6146266

Descriptive statistics

Standard deviation1.5329466
Coefficient of variation (CV)0.49477724
Kurtosis2.9916358
Mean3.0982561
Median Absolute Deviation (MAD)0.74869779
Skewness1.5311548
Sum1143.2565
Variance2.3499252
MonotonicityNot monotonic
2024-07-06T10:57:20.756012image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.046439716 1
 
0.3%
1.78219215 1
 
0.3%
1.746211738 1
 
0.3%
3.040988663 1
 
0.3%
4.001956085 1
 
0.3%
4.558337888 1
 
0.3%
4.937837281 1
 
0.3%
5.188110002 1
 
0.3%
5.420976107 1
 
0.3%
4.818262532 1
 
0.3%
Other values (359) 359
95.0%
(Missing) 9
 
2.4%
ValueCountFrequency (%)
0.7065526953 1
0.3%
0.7464511512 1
0.3%
0.7770942862 1
0.3%
0.997711032 1
0.3%
1.007812161 1
0.3%
1.141057073 1
0.3%
1.146558179 1
0.3%
1.149849541 1
0.3%
1.203617492 1
0.3%
1.212298882 1
0.3%
ValueCountFrequency (%)
9.70768208 1
0.3%
9.590580109 1
0.3%
8.995092392 1
0.3%
8.971839121 1
0.3%
8.529783193 1
0.3%
8.111752601 1
0.3%
7.894354199 1
0.3%
7.78600246 1
0.3%
7.680089739 1
0.3%
7.105134617 1
0.3%

MA_20
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct359
Distinct (%)100.0%
Missing19
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean177.06901
Minimum135.779
Maximum210.983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:20.936755image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum135.779
5-th percentile150.3136
Q1170.9775
median178.6835
Q3188.1605
95-th percentile193.97495
Maximum210.983
Range75.204001
Interquartile range (IQR)17.182999

Descriptive statistics

Standard deviation14.225748
Coefficient of variation (CV)0.080340133
Kurtosis0.19255114
Mean177.06901
Median Absolute Deviation (MAD)9.1139992
Skewness-0.64693384
Sum63567.774
Variance202.3719
MonotonicityNot monotonic
2024-07-06T10:57:21.118080image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188.187999 1
 
0.3%
188.1179993 1
 
0.3%
188.1649994 1
 
0.3%
188.4339996 1
 
0.3%
188.7969994 1
 
0.3%
189.5415001 1
 
0.3%
190.2654999 1
 
0.3%
190.8675003 1
 
0.3%
191.3235008 1
 
0.3%
191.6730003 1
 
0.3%
Other values (349) 349
92.3%
(Missing) 19
 
5.0%
ValueCountFrequency (%)
135.7789993 1
0.3%
136.796999 1
0.3%
138.0199993 1
0.3%
139.4939995 1
0.3%
140.5994995 1
0.3%
141.8244995 1
0.3%
142.8839996 1
0.3%
143.7529991 1
0.3%
144.6329987 1
0.3%
145.5874992 1
0.3%
ValueCountFrequency (%)
210.9830002 1
0.3%
209.4595001 1
0.3%
208.0995003 1
0.3%
206.7875 1
0.3%
205.5625 1
0.3%
204.5959999 1
0.3%
203.4054993 1
0.3%
202.2424995 1
0.3%
201.287999 1
0.3%
200.2249992 1
0.3%

Volatility_20
Real number (ℝ)

MISSING 

Distinct359
Distinct (%)100.0%
Missing19
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean4.4457672
Minimum2.0074068
Maximum10.277889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-07-06T10:57:21.335597image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2.0074068
5-th percentile2.4611607
Q13.0187926
median3.8982488
Q35.3091125
95-th percentile8.3876443
Maximum10.277889
Range8.2704825
Interquartile range (IQR)2.29032

Descriptive statistics

Standard deviation1.844095
Coefficient of variation (CV)0.41479791
Kurtosis0.53601258
Mean4.4457672
Median Absolute Deviation (MAD)1.0112184
Skewness1.1146045
Sum1596.0304
Variance3.4006863
MonotonicityNot monotonic
2024-07-06T10:57:21.529505image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.716801474 1
 
0.3%
4.61875227 1
 
0.3%
4.684888309 1
 
0.3%
5.031703877 1
 
0.3%
5.301245993 1
 
0.3%
5.440700631 1
 
0.3%
5.574439578 1
 
0.3%
5.728447551 1
 
0.3%
5.648666323 1
 
0.3%
5.529309235 1
 
0.3%
Other values (349) 349
92.3%
(Missing) 19
 
5.0%
ValueCountFrequency (%)
2.007406816 1
0.3%
2.073079146 1
0.3%
2.099920143 1
0.3%
2.103446065 1
0.3%
2.124086832 1
0.3%
2.127306029 1
0.3%
2.216914316 1
0.3%
2.25644592 1
0.3%
2.270771667 1
0.3%
2.325729754 1
0.3%
ValueCountFrequency (%)
10.27788934 1
0.3%
10.22548723 1
0.3%
10.09407565 1
0.3%
9.863836597 1
0.3%
9.632940923 1
0.3%
9.505026532 1
0.3%
9.478695098 1
0.3%
9.236876034 1
0.3%
8.770866715 1
0.3%
8.632305054 1
0.3%

Return
Real number (ℝ)

HIGH CORRELATION 

Distinct377
Distinct (%)100.0%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean0.0016674263
Minimum-0.048020049
Maximum0.072649126
Zeros1
Zeros (%)0.3%
Negative170
Negative (%)45.0%
Memory size5.9 KiB
2024-07-06T10:57:22.236085image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-0.048020049
5-th percentile-0.019151671
Q1-0.0069115526
median0.0015789662
Q30.0087824965
95-th percentile0.021888773
Maximum0.072649126
Range0.12066917
Interquartile range (IQR)0.015694049

Descriptive statistics

Standard deviation0.013682661
Coefficient of variation (CV)8.2058565
Kurtosis3.0947743
Mean0.0016674263
Median Absolute Deviation (MAD)0.0078142139
Skewness0.52598862
Sum0.62861973
Variance0.00018721522
MonotonicityNot monotonic
2024-07-06T10:57:22.633221image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.002226290179 1
 
0.3%
-0.003222547374 1
 
0.3%
0.00567140032 1
 
0.3%
-0.002263409002 1
 
0.3%
0.02417488166 1
 
0.3%
-0.004013033762 1
 
0.3%
-0.01270011581 1
 
0.3%
-0.007487607166 1
 
0.3%
-0.03578662771 1
 
0.3%
-0.005424129775 1
 
0.3%
Other values (367) 367
97.1%
ValueCountFrequency (%)
-0.04802004898 1
0.3%
-0.04085746419 1
0.3%
-0.03579332312 1
0.3%
-0.03578662771 1
0.3%
-0.02924939039 1
0.3%
-0.02844095267 1
0.3%
-0.0266798246 1
0.3%
-0.02617044149 1
0.3%
-0.02538126164 1
0.3%
-0.02460553222 1
0.3%
ValueCountFrequency (%)
0.07264912559 1
0.3%
0.05981625254 1
0.3%
0.04692692173 1
0.3%
0.04327091763 1
0.3%
0.03706260689 1
0.3%
0.03679410172 1
0.3%
0.0350900897 1
0.3%
0.03410363052 1
0.3%
0.03257068341 1
0.3%
0.02910457233 1
0.3%

Target
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size24.4 KiB
1
206 
0
172 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters378
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 206
54.5%
0 172
45.5%

Length

2024-07-06T10:57:22.887264image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-06T10:57:23.130138image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
1 206
54.5%
0 172
45.5%

Most occurring characters

ValueCountFrequency (%)
1 206
54.5%
0 172
45.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 378
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 206
54.5%
0 172
45.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 378
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 206
54.5%
0 172
45.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 378
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 206
54.5%
0 172
45.5%

Interactions

2024-07-06T10:57:14.943689image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:00.578897image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.979512image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.147337image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.402964image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.643581image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.791889image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.270839image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.682855image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.795616image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.008544image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.702704image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.037854image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:00.706012image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.065598image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.251864image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.496024image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.733278image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.913785image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.382466image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.768208image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.889489image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.146838image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.843754image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.133319image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:00.821770image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.153743image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.358931image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.584341image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.826323image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.040950image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.495377image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.853371image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.985262image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.261054image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.944355image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.232865image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:00.934813image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.251033image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.472884image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.681141image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.923583image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.165217image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.617614image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.945374image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.073159image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.396756image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.062286image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.333633image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.050762image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.358513image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.578544image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.771485image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.023627image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.285253image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.733807image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.032609image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.174112image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.511886image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.150743image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.431103image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.169320image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.467594image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.687286image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.862906image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.111774image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.412396image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.849007image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.121596image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.281719image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.633771image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.248225image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.541075image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.364940image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.586949image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.811895image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.968333image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.216779image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.543987image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.972397image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.223820image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.403338image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.774908image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.357433image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.645897image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.478372image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.683959image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.917835image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.182162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.315973image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.672369image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.193313image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.329350image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.510035image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:12.908000image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.460162image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.739629image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.573252image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.766359image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.005458image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.264197image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.400965image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.783683image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.282181image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.411137image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.609679image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.057878image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.564717image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.834007image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.663801image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.858134image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.101793image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.355317image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.488272image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:07.904664image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.375062image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.497709image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.707016image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.186141image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.652377image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:15.947889image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.773080image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:02.958749image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.208683image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.450221image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.599035image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.028492image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.483735image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.607455image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.810176image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.439515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.760230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:16.045187image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:01.877337image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:03.049397image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:04.303335image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:05.543836image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:06.688186image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:08.146308image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:09.578055image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:10.705151image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:11.900878image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:13.559049image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-06T10:57:14.849747image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-07-06T10:57:23.265319image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
CloseHighLowMA_10MA_20OpenReturnTargetVolatility_10Volatility_20Volumelow-highopen-close
Close1.0000.9960.9960.9470.8790.9910.0410.076-0.0270.139-0.2170.0450.021
High0.9961.0000.9960.9520.8840.996-0.0050.131-0.0200.141-0.1960.0090.079
Low0.9960.9961.0000.9490.8800.9960.0000.074-0.0280.139-0.2320.0730.077
MA_100.9470.9520.9491.0000.9640.953-0.0780.032-0.0270.138-0.161-0.0140.125
MA_200.8790.8840.8800.9641.0000.884-0.0650.0000.0070.153-0.104-0.0820.102
Open0.9910.9960.9960.9530.8841.000-0.0500.099-0.0220.141-0.2210.0430.136
Return0.041-0.0050.000-0.078-0.065-0.0501.0000.0000.0320.0640.078-0.061-0.798
Target0.0760.1310.0740.0320.0000.0990.0001.000-0.0220.0710.051-0.005-0.042
Volatility_10-0.027-0.020-0.028-0.0270.007-0.0220.032-0.0221.0000.4880.298-0.1960.012
Volatility_200.1390.1410.1390.1380.1530.1410.0640.0710.4881.0000.126-0.156-0.024
Volume-0.217-0.196-0.232-0.161-0.104-0.2210.0780.0510.2980.1261.000-0.615-0.076
low-high0.0450.0090.073-0.014-0.0820.043-0.061-0.005-0.196-0.156-0.6151.0000.049
open-close0.0210.0790.0770.1250.1020.136-0.798-0.0420.012-0.024-0.0760.0491.000

Missing values

2024-07-06T10:57:16.206720image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-06T10:57:16.450491image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-07-06T10:57:16.672412image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

OpenHighLowCloseVolumeopen-closelow-highMA_10Volatility_10MA_20Volatility_20ReturnTarget
Date
2023-01-03130.279999130.899994124.169998125.0700001121175005.209999-6.729996NaNNaNNaNNaNNaN1
2023-01-04126.889999128.660004125.080002126.360001891136000.529999-3.580002NaNNaNNaNNaN0.0103140
2023-01-05127.129997127.769997124.760002125.019997809627002.110001-3.009995NaNNaNNaNNaN-0.0106051
2023-01-06126.010002130.289993124.889999129.61999587754700-3.609993-5.399994NaNNaNNaNNaN0.0367941
2023-01-09130.470001133.410004129.889999130.149994707908000.320007-3.520004NaNNaNNaNNaN0.0040891
2023-01-10130.259995131.259995128.119995130.72999663896200-0.470001-3.139999NaNNaNNaNNaN0.0044561
2023-01-11131.250000133.509995130.460007133.49000569458900-2.240005-3.049988NaNNaNNaNNaN0.0211120
2023-01-12133.880005134.259995131.440002133.410004713796000.470001-2.819992NaNNaNNaNNaN-0.0005991
2023-01-13132.029999134.919998131.660004134.75999557809700-2.729996-3.259995NaNNaNNaNNaN0.0101191
2023-01-17134.830002137.289993134.130005135.94000263646600-1.110001-3.159988130.4549993.982377NaNNaN0.0087560
OpenHighLowCloseVolumeopen-closelow-highMA_10Volatility_10MA_20Volatility_20ReturnTarget
Date
2024-06-21210.389999211.889999207.110001207.4900052464214002.899994-4.779999208.5090007.786002200.22499910.225487-0.0104441
2024-06-24207.720001212.699997206.589996208.13999980727000-0.419998-6.110001209.6340006.650608201.2879999.8638370.0031331
2024-06-25209.149994211.380005208.610001209.070007567139000.079987-2.770004211.2290013.337343202.2425009.6329410.0044681
2024-06-26211.500000214.860001210.639999213.25000066213200-1.750000-4.220001211.8390013.054429203.4054999.4786950.0199931
2024-06-27214.690002215.740005212.350006214.100006497727000.589996-3.389999211.9420013.117273204.5960009.2368760.0039860
2024-06-28215.770004216.070007210.300003210.619995825427005.150009-5.770004211.5800003.029722205.5625008.770867-0.0162541
2024-07-01212.089996217.509995211.919998216.75000060402900-4.660004-5.589996212.0060003.443173206.7875008.5210540.0291051
2024-07-02216.149994220.380005215.100006220.27000458046200-4.120010-5.279999212.3660004.108850208.0995008.4733520.0162401
2024-07-03220.000000221.550003219.029999221.55000337369800-1.550003-2.520004213.0920015.025681209.4595008.3320290.0058111
2024-07-05221.649994226.449997221.649994226.33999660330900-4.690002-4.800003214.7580026.354607210.9830008.5004240.0216200